Dennis Hecker

The paper benchmarks machine learning models for predicting gene expression from epigenomic data using the IHEC EpiATLAS dataset and identifies genes linked to B-cell leukemia.

EpiATLAS provides a comprehensive collection of human reference epigenomes to advance epigenomic research and understanding of cellular function and disease.

The paper introduces MetaFR, a method that links scATAC-seq open-chromatin variation to scRNA-seq gene expression, showing improved performance over existing methods.

The paper identifies Parkinson's disease-associated regulatory variants in human dopaminergic neurons and shows they modulate SCARB2 and BAG3 expression.

The paper identifies 1,580 cell type-specific genes and non-coding RNAs associated with coronary artery disease by integrating genetic and epigenetic data from multiple cell types.

The paper reconstructs metabolic networks across 58 human tissues and cell types using RNA-seq and epigenomic data, identifying core and cell-type-specific metabolic functions and their regulatory elements.

This study shows that loss of KDM6A in hematopoietic cells impairs cardiac recovery after heart failure by causing epigenetic changes in myeloid cells that increase inflammation and worsen cardiac outcomes.

The paper identifies reduced STAT3 expression in cardiac pericytes in HFpEF and shows its loss leads to senescence and impaired adhesion.

The paper adapts the ABC model for enhancer-gene assignment, improves accuracy by incorporating TF binding and single-cell data, and introduces the STARE pipeline.

This study shows that DOT1L regulates specific gene networks in cardiac development and cell cycle withdrawal through H3K79me2 modifications.